Sampling distributions are fundamental for statistical inference, yet their abstract nature poses challenges for students. This research investigates the development of high school students' conceptions of sampling distribution through informal significance tests with the aid of digital technology. The study focuses on how technological tools…

The goal of this article is to introduce the topic of "learning to reason from samples," which is the focus of this special issue of "Educational Studies in Mathematics" on "statistical reasoning." Samples are data sets, taken from some wider universe (e.g., a population or a process) using a particular procedure…

This research investigates what students' use of statistical language can tell us about their conceptions of distribution and sampling in relation to informal inference. Prior research documents students' challenges in understanding ideas of distribution and sampling as tools for making informal statistical inferences. We know that these…

Currently, instruction pays little attention to the development of students' sampling variability reasoning in relation to statistical inference. In this paper, we briefly discuss the especially designed sampling variability learning experiences students aged about 15 engaged in as part of a research project. We examine assessment and…

The expanding use of data in modern society for prediction and decision-making makes it a priority for mathematics instruction to help students build sound foundations of inferential reasoning at a young age. This study contributes to the emerging research literature on the early development of informal inferential reasoning through the conduct of…

Distinguishes two conceptions of sample and sampling that emerged in the context of a teaching experiment conducted in a high school statistics class. Suggests that the conception of a sample as a quasi- proportional, small-scale version of the population is a powerful one to target for instruction. (Author/KHR)